Distributed Course Allocation with Asymmetric Friendships

IF 2.6 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Lihi Dery, Tal Grinshpoun, Ilya Khakhiashvili
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引用次数: 0

Abstract

Students’ decisions on whether to take a class are strongly affected by whether their friends plan to take the class with them. A student may prefer to be assigned to a course they like less, just to be with their friends, rather than taking a more preferred class alone. It has been shown that taking classes with friends positively affects academic performance. Thus, academic institutes should prioritize friendship relations when assigning course seats. The introduction of friendship relations results in several non-trivial changes to current course allocation methods. This paper explores how course allocation mechanisms can account for friendships between students and provide a unique, distributed solution. Specifically, we approach the problem by framing it as an asymmetric distributed constraint optimization problem and develop a new dedicated algorithm. Our extensive evaluation includes both simulated data and a study involving 177 students, focusing on their preferences regarding both courses and friendships. The findings indicate that our algorithm achieves significant utility for the students, maintaining fairness in the solution and adhering to the limitations on course seat capacities.

基于非对称友谊的分布式课程分配
学生决定是否上一门课很大程度上取决于他们的朋友是否计划和他们一起上这门课。学生可能更愿意被分配到他们不太喜欢的课程,只是为了和朋友在一起,而不是独自参加更喜欢的课程。研究表明,和朋友一起上课对学习成绩有积极影响。因此,学术机构在分配课程时应该优先考虑友谊关系。友谊关系的引入给当前的课程分配方法带来了一些重要的变化。本文探讨了课程分配机制如何能够考虑到学生之间的友谊,并提供一个独特的分布式解决方案。具体来说,我们将该问题视为一个非对称分布约束优化问题,并开发了一种新的专用算法。我们广泛的评估包括模拟数据和一项涉及177名学生的研究,重点关注他们对课程和友谊的偏好。研究结果表明,我们的算法对学生的效用显著,既保持了解决方案的公平性,又遵守了课程座位数的限制。
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来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
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